A meta-analysis on the relationship between school characteristics and student outcomes in science and maths – evidence from large-scale studies

TL;DR: In this article , the authors used data from 729 ninth graders to investigate how student-observed learning activities when using technology at a distance were related to students' effort in learning in two subjects (mathematics, German).

TL;DR: In this paper, the relevance of the school context to creating a successful learning environment and promoting teachers' instructional quality is not yet clear, and the authors examine whether schools have the ability to create successful learning environments and promote teacher's instructional quality.

TL;DR: In this article, the authors examined the relative effects of student, family and school-related characteristics on 4th grade students' math achievement according to location of the school in Turkey, and the results revealed that the entire models explained the largest amount of variance (52%) in the schools located in the villages and the least amount of variances (44%) in those located in an urban area.

TL;DR: It is indicated that a series of stand-alone diagrams can effectively be used by teachers to assess how students communicate their understanding of causal explanations in terms of sub-microscopic entities of the underlying phenomena.

TL;DR: A structured summary is provided including, as applicable, background, objectives, data sources, study eligibility criteria, participants, interventions, study appraisal and synthesis methods, results, limitations, conclusions and implications of key findings.

TL;DR: Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials.

TL;DR: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is introduced, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses.

TL;DR: The metafor package provides functions for conducting meta-analyses in R and includes functions for fitting the meta-analytic fixed- and random-effects models and allows for the inclusion of moderators variables (study-level covariates) in these models.